Structure-based computer-aided drug design to identify potential lead molecules for Asparaginyl Endopeptidase inhibitors.

The enzyme Asparaginyl Endopeptidase (AEP) is associated with proteinopathy-related pathologies such as Alzheimer's disease (AD) and Frontal Temporal Dementia (FTD). The onset of pathologies by AEP is due to cleaved fragments forming protein aggregates resulting in neurodegeneration. Unfortunately, there are no clinically approved small molecule inhibitors for AEP, and therefore, it serves as an unmet medical need for the design and development of potential novel small molecules. In developing potential inhibitors for proteolytic activity, a structured approach utilizing structure-based computer-aided drug design (SB-CADD) parameters was employed. This involved virtual high throughput screening (vHTS) across various CNS-focused databases enriched with diverse functionality. We identified the top sixty ligands based on the glide XP-docking score out of 10 million ligands. The free binding energy was then calculated using MM-GBSA for all top selected molecules which resulted in discovering that AEPI-1 to AEPI-6 (Asparaginyl Endopeptidase inhibitors) displayed high affinity towards the catalytic triad. Further investigation determined that all top six hits form stable complexes during 50 ns molecular dynamic simulations. We also observed that AEPI-2 demonstrated the highest stability within the binding pockets. Post-MD analyses such as DCCM, PCA, PDF, and ADMET properties were also evaluated. By bridging all the observations, we observed these six molecules occupy the active site of the β-helix (β1, β3, and β4) of the S1 pocket and additional binding sites in α1 and β5, suggesting its suitability as a potential candidate for drug discovery against Asparaginyl Endopeptidase.